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Record W1599065150 · doi:10.1353/eca.2016.0005

Grasp the Large, Let Go of the Small: The Transformation of the State Sector in China

2016· article· en· W1599065150 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBrookings Papers on Economic Activity · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsBooth University College
Fundersnot available
KeywordsGRASPChinaTransformation (genetics)State (computer science)Political scienceComputer scienceChemistryLaw

Abstract

fetched live from OpenAlex

In the late 1990s, China’s industrial sector was dominated by state-owned firms. We document how this changed after 1998. More than 80 percent of the state-owned firms in 1998 were shut down or privatized by 2007. Among firms we classify as state-controlled in 2007, many were restructured and registered as private firms with a controlling share held by a state-owned conglomerate or were new firms established after 1998. In 2007, almost half of the state-controlled firms were registered as private firms, and about 40 percent were new firms established after 1998. The privatization and convergence in labor productivity decelerated after 2007, but the establishment of new state-owned firms continued at roughly the same rate. When we interpret these facts through the lens of an equilibrium model of heterogeneous firms, we find that the transformation of firms that remained under state control and the creation of new state-controlled firms together account for 21 percent of China’s growth from 1998 to 2007 and 18 percent of its growth from 2007 to 2012. However, the exit and privatization of state-owned firms had a negligible effect on aggregate growth.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.370
Threshold uncertainty score0.376

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.185
Teacher spread0.163 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it